Counts by Wave

Counts the number of datapoints in the criterion availibe at each time interval.

by Wave : ELSA

by Wave : OCTO

by Wave : RUSHc

by Wave : RUSHe

by Wave : RUSHl

Counts by Age

Counts the number of datapoints in the criterion availibe at each time interval. ## by Age : ELSA

by Age : OCTO

by Age : RUSHc

by Age : RUSHe

by Age : RUSHl

Observed Trajectories (Time)

Transparent blue lines represent observed trajectories. A random sample was selected from the study’s data to avoid overplotting. Solid red line represents the fixed effects of the intercept and slope that are quantified in the equation in the top right corner.

by Time : ELSA

by Time : OCTO

by Time : RUSHc

by Time : RUSHe

by Time : RUSHl

Observed Trajectories (Age)

The legend is the same as in the plot of observed trajectories. This is the same model (using TIME IN STUDY to predict the outcome), however in this graph the trajectories are re-distributed over a different metric of time: Age in years at the time of the interview.

by Age : ELSA

by Age : OCTO

by Age : RUSHc

by Age : RUSHe

by Age : RUSHl

Predicted Trajectories (Time)

The legend is the same as in the plots above. Semi-transparent blue lines represent the model prediction for each individual, computed from the estimated unique slopes and variances.

by Time : ELSA

by Time : OCTO

by Time : RUSHc

by Time : RUSHe

by Time : RUSHl

Predicted Trajectories (Age)

The legend is the same as in the plots above. Semi-transparent blue lines represent the model prediction for each individual, computed from the estimated unique slopes and variances.This is the same model as above, only the trajectories are re-distributed over a different metric of time: Age in years at the time of the interview.

by Age : ELSA

by Age : OCTO

by Age : RUSHc

by Age : RUSHe

by Age : RUSHl














\({y_{ti}} = {\beta _{0i}} + {\beta _{1i}}Tim{e_{ti}} + {\varepsilon _{ti}}\\ \\ {\beta _{0i}} = {\gamma _{0.0}} + {\gamma _{0.1}}SE{X_i} + {\gamma _{0.2}}AG{E_i} + {\gamma _{0.3}}E{D_i} + {\gamma _{0.4}}SMOKE{D_i} + {\gamma _{0.5}}CH{F_i} + {\gamma _{0.6}}M{I_i} + {\gamma _{0.7}}ST{K_i} + {\gamma _{0.7}}HP{N_i} + \\ + {\gamma _{0.8}}D{M_i} + {\gamma _{0.9}}HTND{M_i} + {\gamma _{0.11}}AGE\_SE{X_i} + {\gamma _{0.12}}AGE\_HT{N_i} + {\gamma _{0.13}}AGE\_D{M_i} + {\gamma _{0.14}}SEX\_HT{N_i} + {\gamma _{0.15}}SEX\_D{M_i} + {u_{0i}}\\ \\ {\beta _{1i}} = {\gamma _{1.0}} + {\gamma _{1.1}}SE{X_i} + {\gamma _{1.2}}AG{E_i} + {\gamma _{1.3}}E{D_i} + {\gamma _{1.4}}SMOKE{D_i} + {\gamma _{1.5}}CH{F_i} + {\gamma _{1.6}}M{I_i} + {\gamma _{1.7}}ST{K_i} + {\gamma _{1.7}}HP{N_i} + \\ + {\gamma _{1.8}}D{M_i} + {\gamma _{1.9}}HTND{M_i} + {\gamma _{1.11}}AGE\_SE{X_i} + {\gamma _{1.12}}AGE\_HT{N_i} + {\gamma _{1.13}}AGE\_D{M_i} + {\gamma _{1.14}}SEX\_HT{N_i} + {\gamma _{1.15}}SEX\_D{M_i} + {u_{1i}}\\\)